上海交通大学学报

上海交通大学学报（自然版） ›› 2015, Vol. 49 ›› Issue (09): 1346-1352.

• 机械仪表工程 • 上一篇    下一篇

砂轮磨削过载判据及其快速诊断

王嗣阳，许黎明，赖小平   

  1. (上海交通大学 机械动力与工程学院,上海 200240)
  • 收稿日期:2014-10-08
  • 基金资助:

    国家自然科学基金资助项目（51075273）

Grinding Wheel Overload Criterion and Diagnosis

WANG Siyang,XU Liming,LAI Xiaoping   

  1. (School of Mechanical Engineering, Shanghai Jiaotong Universty, Shanghai 200240, China)
  • Received:2014-10-08

摘要：

摘要：  基于对砂轮磨削过程中声发射信号的采集，研究了2种砂轮磨削过载判据的特征量提取方法，并提出了评价砂轮磨削过载判据的主要指标即灵敏度、稳定性和算法效率.通过选取合理的采样率与处理间隔，分析比较了2种信号处理方法对砂轮与工件过载的识别效果.结果表明，所提出的信噪特征比方法提取的特征量具有稳定性好、灵敏度和算法效率高的特点，且可以对过载点实现预判，可作为优先选择的磨削过载判据.

关键词: 磨削防过载, 特征提取, 声发射, 诊断

Abstract:

Abstract： Based on the acquisition of acoustic emission signal in the grinding process, two feature extraction methods for establishing grinding overload criterion were studied. The main indicators of sensitivity, stability and algorithm efficiency were proposed to evaluate the performance of different antioverload criterions. The effects of different signal processing methods on identifying the overload point between wheel and workpiece were analyzed with grinding experiments. The results show that the proposed feature extraction method of signaltonoise ratio which has high sensitivity, high algorithm efficiency and good stability, can predict the overload to some extent and can be used as the prior overload diagnosis criterion.
 

Key words: grinding anti-overload, feature extraction, acoustic emission, diagnosis

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